Earticle

초록

영어

Data Mining is a popular knowledge discovery technique. In data mining decision trees are of the simple and powerful decision making models. One of the limitations in decision trees is towards the data source which they tackle. If data sources which are given as input to decision tree are of imbalance nature then the efficiency of decision tree drops drastically, we propose a decision tree structure which uses discrete haar wavelet transformation technique along with a filter. In this paper, we propose a novel method WT Tree based on above strategy. Extensive experiments, using C4.5 decision tree as base classifier, show that the performance measures of our method is comparable to state-of-the-art methods.

목차

Abstract
 1. Introduction
 2. Recent Advances in Decision Trees
 3. Proposed Method
  3.1. Wavelet Transform
  3.2. Wavelet Transform Decision Tree Framework
 4. Experimental Design and Evaluation Criteria's
 5. Results
 6. Conclusion
 References

키워드

저자

• Bhanu Prakash Battula [ Department of Computer Science and Engineering, Vignan’sNirula Institute of Technology and Science, Guntur, Andhra Pradesh, India ]
• KVSS Rama Krishna [ Department of Computer Science and Engineering, Vignan’sNirula Institute of Technology and Science, Guntur, Andhra Pradesh, India ]
• Debnath Bhattacharyya [ Department of Information Technology, BharatiVidyapeeth University College of Engineering, Pune-411043, India ]
• Tai-hoon Kim [ Department of Convergence Security, Sungshin Women's University, 249-1, Dongseon-dong 3-ga, Seoul, 136-742, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605